1. Computer Arithmetic Programming in C++ Computer Science Dept Va Tech August, 2000 ©1995-2000 Barnette ND, McQuain WD, Keenan MA 1 Independent Representation Integer On standard 32 bit machines:INT_MAX = 2147483647 which gives 10 digits of precision, (i.e. the maximum number of significant digits). Range is the interval from the smallest representable value to the largest representable value. + 1 2 3 4 5 6 7 8 9 0 sign magnitude Float + + 0 1 2 3 4 5 6 7 8 sign of mantissa sign of exponent Real numbers are stored in a normalized format, (the first digit of the mantissa is nonzero).

2. Computer Arithmetic Programming in C++ Computer Science Dept Va Tech August, 2000 ©1995-2000 Barnette ND, McQuain WD, Keenan MA 2 Arithmetic Errors Storage The representation to the right corresponds to the real number(s): 2.345678 2.3456789 2.34567891 + + 0 1 2 3 4 5 6 7 8 sign of mantissa sign of exponent + + 0 1 2 3 4 5 6 7 9 The last two, not represented exactly due to limited precision, are examples of representational, (truncation), error. Some machines round instead of truncate and would thus represent the last 2 numbers as shown at the right. The difference between the actual value and the rounded value introduces rounding error.

3. Computer Arithmetic Programming in C++ Computer Science Dept Va Tech August, 2000 ©1995-2000 Barnette ND, McQuain WD, Keenan MA 3 Arithmetic Errors Operations The addition, 0.9999999 x 10 99 + 1, results in an overflow error, an attempt to represent a number larger than the maximum representable value. Analogously, underflow is an attempt to represent a number smaller than the minimum representable value. Integer overflow & underflow occurs when an expression evaluates to a value outside the range [ INT_MIN... INT_MAX ]. The C++ reference manual states that the result of overflow is undefined, (i.e. compiler dependent). The manual states that the result of underflow is also undefined, (compiler dependent).

4. Computer Arithmetic Programming in C++ Computer Science Dept Va Tech August, 2000 ©1995-2000 Barnette ND, McQuain WD, Keenan MA 4 Arithmetic Errors Operations Consider the simple problem of summing real numbers stored in a file one per line, (example given at right). The result after the first three additions would be 3000000.0. The second & fourth numbers having no effect on the result due to limited precision & the large differences in the numbers, termed cancellation error. 1000000.0 0.000123 2000000.0 0.000456 In the worst case, if the entire file was organized in this manner only half of the numbers would be added. Solution: sort the numbers & add the smallest first so they may affect the total.

5. Computer Arithmetic Programming in C++ Computer Science Dept Va Tech August, 2000 ©1995-2000 Barnette ND, McQuain WD, Keenan MA 5 Considerations Comparisons Due to representational errors, (and conversion errors), float values should never be compared for equality. Looping For the same reasons float variables should not be used for loop control. Float Equality Check abs ( real1 - real2 ) < epsilon where epsilon = 0.00001 an appropriate value near the precision of the machine. Float Equality Check abs ( real1 - real2 ) < epsilon where epsilon = 0.00001 an appropriate value near the precision of the machine. // loop from 0.0 to 1.0 in increments of 0.1 float realVar = 0.0 ; while ( realVar < 1.0 ) { // realVar = realVar + 0.1 ; } Dangerous // loop from 0.0 to 1.0 in increments of 0.1 i = 0 ; while ( i < 10 ) { realVar = i / 10.0 ; // i = i + 1 ; } Better

6. Computer Arithmetic Programming in C++ Computer Science Dept Va Tech August, 2000 ©1995-2000 Barnette ND, McQuain WD, Keenan MA 6 Floats as LCVs The short program below illustrates the perils of direct comparison of float values. Logically the variable X should take on values 0.000, 0.001, 0.002,..., 0.999, 1.000. However, when executed on a Pentium II cpu, the program produces output as shown below. #include using namespace std; void main() { float X = 0.0f; float DeltaX = 0.001f; int Counter = 0; cout.setf(ios::fixed, ios::floatfield); cout.setf(ios::showpoint); while (X < 1.0) { cout << setw( 4) << Counter << setw(10) << setprecision(5) << X << endl; X = X + DeltaX; Counter++; } cout << setw( 4) << Counter << setw(10) << setprecision(5) << X << endl; } 993 0.99299 994 0.99399 995 0.99499 996 0.99599 997 0.99699 998 0.99799 999 0.99899 1000 0.99999 1001 1.00099 An infinite loop would result if the condition were changed to X != 1.0

7. Computer Arithmetic Programming in C++ Computer Science Dept Va Tech August, 2000 ©1995-2000 Barnette ND, McQuain WD, Keenan MA 7 Float Underflow The short program below illustrates a float variable underflowing to zero. Logically the while loop should be infinite. However, when executed on a Pentium II cpu, the program produces output as shown below. #include using namespace std; void main() { const float One = 1.0f; float X = 1.0f; int Counter = 1; cout.setf(ios::fixed, ios::floatfield); cout.setf(ios::showpoint); while (X != 0.0f) { cout << setw( 3) << Counter << setw(15) << setprecision(6) << X << endl; X = X / 2.0f; Counter++; } 1 1.000000 2 0.500000 3 0.250000 4 0.125000 5 0.062500 6 0.031250 7 0.015625 8 0.007813 9 0.003906 10 0.001953 11 0.000977 12 0.000488 13 0.000244 14 0.000122 15 0.000061 16 0.000031 17 0.000015 18 0.000008 19 0.000004 20 0.000002 21 0.000001 22 0.000000... 149 0.000000 150 0.000000

8. Computer Arithmetic Programming in C++ Computer Science Dept Va Tech August, 2000 ©1995-2000 Barnette ND, McQuain WD, Keenan MA 8 Machine Epsilon The short program below illustrates a float variable underflowing to zero. Logically the while loop should be infinite. However, when executed on a Pentium II cpu, the program produces output as shown below. #include using namespace std; void main() { const float One = 1.0f; float X = 1.0f; int Counter = 1; cout.setf(ios::fixed, ios::floatfield); cout.setf(ios::showpoint); while (One + X != One) { cout << setw( 3) << Counter << setw(15) << setprecision(6) << X << endl; X = X / 2.0f; Counter++; } 1 1.000000 2 0.500000 3 0.250000 4 0.125000 5 0.062500 6 0.031250 7 0.015625 8 0.007813 9 0.003906 10 0.001953 11 0.000977 12 0.000488 13 0.000244 14 0.000122 15 0.000061 16 0.000031 17 0.000015 18 0.000008 19 0.000004 20 0.000002 21 0.000001 22 0.000000... 52 0.000000 53 0.000000